With the development of power systems, smart grid has become the tendency of the future power industry development, and smart meters are increasingly deployed. At present, most smart meters can record electricity consumption information of users every 15 minutes. Moreover, with the continuous development of related technologies, the smart meters can record electricity consumption information at a higher frequency to form high-dimensional time series data, which will undoubtedly bring huge transmission burden to communication lines and also will bring huge storage cost to a data center. In addition, it will be very difficult to analyze and apply such high-dimensional big data from the smart meters, such as electricity load prediction, abnormal electricity consumption detection, demand side management and etc. Therefore, the compression of data from the smart meters is of great importance to reduce the transmission burden for communication lines and storage burden for the data center and to improve the efficiency of smart electricity data analysis and service.
However, at present, there is no compression method or system that can have high compression rate to relieve the data transmission burden and reduce storage cost, as well as improve the efficiency of big data analysis and mining.